Region-Based Saliency Detection and Its Application in Object Recognition

By Zhixiang Ren, Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang. IEEE transactions on circuits and systems for video technology (Print), 2014

329 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/2949695c568e38fa0181feece7fed970af91046c

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In Computer Vision and Pattern Recognition

Citations in the corpus

Salient Object Detection in the Deep Learning Era: An In-Depth Survey (2019, neutral): “In computer vision, sampled applications of SOD include image understanding [1], [2], image cap-tioning [3]–[5], object detection [6], [7], un-supervised video object segmentation [8], [9], semantic segmentation [10]– [12], person re-identiﬁcation [13], [14], etc .”
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup (2020, methodology): “The saliency information has been used in various ﬁelds of machine learning (Ren et al., 2013; Wei et al., 2017).”
Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection (2018, background): “Salient object detection is useful for a large range of computer vision and robotic vision tasks such as object recognition [4], image retrieval [5] and SLAM [6].”
Salient Object Detection: A Benchmark (2015, methodology): “For instance, these models have been successfully applied in many applications such as object detection and recognition [22]–[29], image and video compres-”
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection (2019, background): “Recently, this fundamental task plays an important role in various computer vision applications [15,21,29,37], e.”
A Bi-Directional Message Passing Model for Salient Object Detection (2018, methodology): “It can be taken as a pre-processing step in many computer vision tasks, such as scene classification [25], visual tracking [3, 21], person re-identification [40] and image retrieval [5].”
Attentive Systems: A Survey (2017, background): “In another work, Ren et al. (2014) apply saliency maps to better encode image features for object recognition.”
Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection (2017, background): “As a pre-processing step in computer vision, saliency detection has shown a great success in ranges of visual applications, e.g . object retargeting [7, 38, 40], scene classiﬁcation [35, 33], visual tracking [4, 29], image retrieval [14, 11] and semantic segmentation [8].”
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection (2019, background): “It has a wide range of applications, including video/image segmentation [17, 40], object recognition [46], visual tracking [ 3], foreground maps evaluation [14, 15], image retrieval [6,16,22,38], content-aware image editing [8], information discovery [58], photo synthesis [5, 29], and weakly…”